Instructions to use waterman3000/peft with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use waterman3000/peft with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("automatic-speech-recognition", model="waterman3000/peft")# Load model directly from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq processor = AutoProcessor.from_pretrained("waterman3000/peft") model = AutoModelForSpeechSeq2Seq.from_pretrained("waterman3000/peft") - Notebooks
- Google Colab
- Kaggle
Upload WhisperForConditionalGeneration
Browse files- model.safetensors +1 -1
model.safetensors
CHANGED
|
@@ -1,3 +1,3 @@
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
-
oid sha256:
|
| 3 |
size 151061672
|
|
|
|
| 1 |
version https://git-lfs.github.com/spec/v1
|
| 2 |
+
oid sha256:098725009c98db4087b1b7db501d940c4a203051b4ec541f3724be6b9bfb8423
|
| 3 |
size 151061672
|